Evidence map›Paper›PMID 39170422›Full record

ArticleHeliyon2024

Investigating the anti-inflammatory effects of icariin: A combined meta-analysis and machine learning study.

Xiaochuan Guo, Yanqin Qin, Zhenzhen Feng, Haibo Li, Jingfan Yang, Kailin Su, Ruixiao Mao, Jiansheng Li

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiaochuan GuoDepartment of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China.
Yanqin QinCo-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases By Henan and Education Ministry of PR China, Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou 450046, Henan province, China.
Zhenzhen FengDepartment of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China.
Haibo LiCo-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases By Henan and Education Ministry of PR China, Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou 450046, Henan province, China.
Jingfan YangCo-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases By Henan and Education Ministry of PR China, Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou 450046, Henan province, China.
Kailin SuDepartment of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China.
Ruixiao MaoDepartment of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China.
Jiansheng LiDepartment of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The objectives of this study were to define the superiority of icariin and its derivatives' anti-inflammatory activities and to create a reference framework for evaluating preclinical evidence. This method combines machine learning and meta-analysis to identify underlying biological pathways. Methods: Data came from PubMed, Embase, Web of Science, and the Cochrane Library. SYRCLE was used to evaluate the risk of bias in a subset of research. Meta-analysis and detailed subgroup analyses, categorized by species, genders, disease type, dosage, and treatment duration, were performed using R and STATA 15.0 software to derive nuanced insights. Employing R software (version 4.2.3) and the tidymodels package, the analysis focused on constructing a model and selecting features, with TNF-α as the dependent variable. This approach aims to identify significant predictors of drug efficacy. An in-depth literature facilitated the synthesis of anti-inflammatory mechanisms attributed to icariin and its constituent compounds. Results: Following a meticulous search and selection process, 19 studies, involving 370 and 260 animals were included in the meta-analysis and machine-learning assessment, respectively. The findings revealed that icariin and its derivatives markedly reduced inflammation markers, including TNF-α and IL-1β. Additionally, machine-learning outcomes, with TNF-α as the target variable, indicated enhanced anti-inflammatory effects of icariin across respiratory, urological, neurological, and digestive disease types. These effects were more pronounced at doses exceeding 27.52 mg/kg/day and treatment durations beyond 31.22 days. Conclusion: Strong anti-inflammatory effects are exhibited by icariiin and its derivatives, which are especially beneficial in the management of digestive, neurological, pulmonary, and urinary conditions. Effective for periods longer than 31.22 days and at dosages more than 27.52 mg/kg/day. Subsequent research will involve more targeted animal experiments and safety assessments to obtain more comprehensive preclinical evidence.

Indexed as

Core mechanismsIcariinInflammationMachine learningMeta-analysisPreclinical evidence

Identifiers

PMID39170422
PMCPMC11336647

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.